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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2
Appearance Based Models in Document Script Identification
Curitiba, Parana, Brazil
September 23-September 26
ISBN: 0-7695-2822-8
ASCII Text
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T.N. Vikram, D.S. Guru, "Appearance Based Models in Document Script Identification," Document Analysis and Recognition, International Conference on, vol. 2, pp. 709-713, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007.
 
 
BibTex
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@article{ 10.1109/ICDAR.2007.59,
author = {T.N. Vikram and D.S. Guru},
title = {Appearance Based Models in Document Script Identification},
journal ={Document Analysis and Recognition, International Conference on},
volume = {2},
year = {2007},
issn = {1520-5363},
pages = {709-713},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.59},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Document Analysis and Recognition, International Conference on
TI - Appearance Based Models in Document Script Identification
SN - 1520-5363
SP709
EP713
A1 - T.N. Vikram,
A1 - D.S. Guru,
PY - 2007
VL - 2
JA - Document Analysis and Recognition, International Conference on
ER -
 
T.N. Vikram, University of Mysore, Manasagangotri, Mysore-570006, India
D.S. Guru, University of Mysore, Manasagangotri, Mysore-570006, India
In this paper we employ appearance based models for document script identification. They are employed to identify scripts at both paragraph and word level. Elaborate experimentation has been conducted which has revealed that they are robust enough to handle highly confusing scripts and their performance does not degrade drastically even in the presence of noise. A generic script identification has been attempted, to identify both Asian and European scripts by considering a dataset of twenty different languages.
Citation:
T.N. Vikram, D.S. Guru, "Appearance Based Models in Document Script Identification," icdar, vol. 2, pp.709-713, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007
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